Job Description:

• Own the lifecycle of our computer vision models, including training, evaluation, deployment, and iteration
• Improve model performance in real-world conditions (noise, edge cases, data drift)
• Design and improve data pipelines that process thousands of miles of sidewalks and millions of images
• Lead architectural decisions for handling hundreds of terabytes of geospatial and visual data, including storage layout, pipeline reliability, and inference performance
• Set and evolve best practices around deployment, observability, system reliability, and scalability
• Act as a senior individual contributor and mentor, helping raise the technical bar across the engineering team
• Work closely with the CEO and operations team to turn business needs into clear technical priorities

Requirements:

• 6+ years of experience, including direct ownership of production ML or computer vision systems (training, deployment, and ongoing operation)
• Experience taking models from training → production → monitoring → iteration in a real-world environment
• Experience owning system architecture and influencing technical decisions across teams
• Experience deploying computer vision or ML systems in real-world production environments
• Fluency in at least one modern backend language (Python, Java, TypeScript, Go, etc.)
• Strong understanding of system design, scalability, and distributed systems
• Experience with cloud platforms such as AWS, GCP, or Azure
• Comfort working in a startup or growth-stage environment with changing requirements.

Benefits:

• $150,000 – $190,000 base salary, based on scope and experience
• Equity
• Unlimited PTO (most of our team takes 3–4 weeks per year)
• Health insurance
• 401(k) with ~4% match (100% on first 3%, 50% on the next 2%)

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